Surprising diversity of new plasmids in bacteria isolated from hemorrhoid patients.

Background: Hemorrhoids are common conditions at or around the anus, to which numerous people suffer worldwide. Previous research has suggested that microbes may play a role in the development of hemorrhoids, and the origins of these microbes have been preliminarily investigated. However, no detailed research on the microbes related to hemorrhoid patients has been conducted. This work aims to provide an initial investigation into the microbes related to hemorrhoid patients with high quality whole genome sequencing. Methods: Forty-nine bacterial strains were isolated from seven hemorrhoid patients. Third-generation nanopore sequencing was performed to obtain high quality whole genome sequences. The presence of plasmids, particularly new plasmids, along with antibiotic resistance genes, was investigated for these strains. Phylogenetic analysis and genome comparisons were performed. Results: Out of the 31 plasmids found in the strains, 15 new plasmids that have not been observed previously were discovered. Further structural analysis revealed new multidrug-resistant conjugative plasmids, virulent plasmids, and small, high-copy mobile plasmids that may play significant functional roles. These plasmids were found to harbor numerous integrases, transposases, and recombinases, suggesting their ability to quickly obtain genes to change functions. Analysis of antibiotic resistance genes revealed the presence of antibiotic resistant-integrons. Together with the surprising number of new plasmids identified, as well as the finding of transmission and modification events for plasmids in this work, we came to the suggestion that plasmids play a major role in genetic plasticity. Conclusion: This study reveals that the diversity of plasmids in human-associated microbes has been underestimated. With the decreasing cost of whole-genome sequencing, monitoring plasmids deserves increased attention in future surveillance efforts.

High efficiency removal of antibiotic resistance gene with designer zinc-finger protein.

The use of agricultural biomass-based fertilizers, and the release of feces into the environment leads to last-lasting pollution of antibiotic resistance genes that cannot be removed from waters via traditional methods, resulting in significant health threats. To solve this issue, an antibiotic resistance gene removal method was proposed and tested that used sequence-specific DNA-binding designer zinc finger proteins, which target an 18-bp DNA sequence for specific antibiotic resistance gene binding and removal. Targeting the sulfonamide-resistant sul1 gene, sul1-binding zinc-finger protein was designed, overexpressed, and purified. This protein showed specific binding with sul1 over tetA that do not have the targeted sequence. This protein was further immobilized on agarose-based resins to prepare a sul1-removal column. When loaded with 10 mg protein, this column can remove over 99 % sul1 in water, suggesting high efficiency. This work presents a new method attempting to eliminate environmental and health threats posed by antibiotic resistance genes.

Mimics of Host Defense Peptides Derived from Dendronized Polylysines for Antibacterial and Anticancer Therapy.

Bacteria in tumor microenvironments promote carcinogenesis and trigger complications, suggesting the significance of intervening in bacterial growth in cancer treatment. Here, dendrimer-derived mimics (DMs) of host defense peptides (HDPs) were designed for antibacterial and anticancer therapy, which feature a dendronized polylysine core and polycaprolactone arms. DMs displayed not only remarkable activities against Staphylococcus aureus and human lung cancer cells, but also exceptional selectivity. The membranolytic mechanism revealed by morphology analysis explained their low susceptibility to induce resistance. Further, the optimized DM inhibited tumor growth in the subcutaneous tumor model when administered via intraperitoneal injection and exhibited negligible toxicity to tissues. Overall, we combined the superiority of dendrimers and the mechanism from HDPs to design agents with dual antibacterial and anticancer activities that possess great potential for clinical oncology therapy.

Low-Solvent-Coordination Solvation Structure for Lithium-Metal Batteries via Electric Dipole-Dipole Interaction.

Unveiling inherent interactions among solvents, Li+ ions, and anions are crucial in dictating solvation-desolvation kinetics at the electrode/electrolyte interface. Developing an electrolyte with a low ion-transport barrier and minimal solvent coordination in its interfacial solvation structure is essential for forming an anion-derived solid-electrolyte interface, a key component for high-performance Li-metal batteries. In this study, we harness electric dipole-dipole synergistic interactions to formulate an electrolyte with significantly reduced interfacial solvent coordination. Operando characterization and theoretical analysis reveal that 2-fluoropyridine (FPy) with high dipole preferentially adsorbs onto the Li metal surface. The adsorbed FPy molecule squeezes succinonitrile in the primary solvation sheath through steric hindrance, leading to the formation of an inorganic-rich interphase. Consequently, the introduction of FPy enhances the reversible capacity of the LiCoO2||Li cell, which maintains a capacity of 143 mAh g-1 after 500 cycles at a 1C rate. Moreover, the cycle life of LiCoO2 batteries with a limited supply of lithium extends from 120 cycles to over 200 cycles. These findings offer a strategy that can be applied broadly to design interfacial solvation structures for various metal-ion/metal-based batteries.

The A226D Mutation of OmpC Leads to Increased Susceptibility to ß-Lactam Antibiotics in Escherichia coli.

Bacterial resistance to antibiotics can lead to long-lasting, hard-to-cure infections that pose significant threats to human health. One key mechanism of antimicrobial resistance (AMR) is to reduce the antibiotic permeation of cellular membranes. For instance, the lack of outer membrane porins (OMPs) can lead to elevated AMR levels. However, knowledge on whether mutations of OMPs can also influence antibiotic susceptibility is limited. This work aims to address this question and identified an A226D mutation in OmpC, a trimeric OMP, in Escherichia coli. Surveillance studies found that this mutation is present in 50 E. coli strains for which whole genomic sequences are available. Measurement of minimum inhibition concentrations (MICs) found that this mutation leads to a 2-fold decrease in MICs for ß-lactams ampicillin and piperacillin. Further survival assays confirmed the role this mutation plays in ß-lactam susceptibility. With molecular dynamics, we found that the A226D mutation led to increased overall flexibility of the protein, thus facilitating antibiotic uptake, and that binding with piperacillin was weakened, leading to easier antibiotic penetration. This work reports a novel mutation that plays a role in antibiotic susceptibility, along with mechanistic studies, and further confirms the role of OMPs in bacterial tolerance to antibiotics.

[Analysis of chemical compositions in different parts of Isodon japonicus using UPLC-Q-TOF-MS technique combined with chemometrics].

In order to analyze the similarities and differences of chemical compositions between the roots and stems and leaves of Isodon japonicus(IJ), this study utilized UPLC-Q-TOF-MS technology to systematically characterize its chemical compositions, analyzed and identified the structure of its main compounds, and established a method for simultaneous determination of its content by refe-rence substance. A total of 34 major compounds in IJ, including 14 reference compounds, were identified or predicted online. Moreover, an UPLC-UV content determination method was developed for 11 compounds [danshensu, caffeic acid, vicenin-2,(1S,2S)-globoidnan B, rutin,(+)-rabdosiin,(-)-rabdosiin,(1S,2S)-rabdosiin, shimobashiric acid C, rosmarinic acid, and pedalitin]. The method exhibited excellent separation, stability, and repeatability, with a wide linear range(0.10-520.00 µg·mL~(-1)) and high linearity(R~2>0.999). The average recovery rates ranged from 94.72% to 104.2%. The principal component analysis(PCA) demonstrated a clear difference between the roots and stems and leaves of IJ, indicating good separation by cluster. Furthermore, the orthogonal partial least squares discriminant analysis(OPLS-DA) model was employed, and six main differentially identified compounds were identified: rosmarinic acid, shimobashiric acid C, epinodosin, pedalitin, rutin, and(1S,2S)-rabdosiin. In summary, this study established a strategy and method for distinguishing different parts of IJ, providing a valuable tool for quality control of IJ and a basis for the ratio-nal utilization and sustainable development of IJ.

Effects of Cu (II) on the Growth of Chlorella vulgaris and Its Removal Efficiency of Pollutants in Synthetic Piggery Digestate.

C. vulgaris has a positive effect on the removal of nutrients from pig farm biogas slurry. However, swine wastewater often contains heavy metal ions, such as Cu (II), which may have impacts on the nutrient removal performance of C. vulgaris. Additionally, the heavy metal ions in wastewater can be adsorbed by microalgae. In this study, the stress effect of Cu (II) on the growth of Chlorella vulgaris, the Cu (II) removal by microalgae, and the effect of different concentrations of Cu (II) on the nutrient removal efficiency of C. vulgaris in biogas slurries were explored. The results showed that the microalgae biomass of microalgae on the sixth day of the experiment was the highest in the treatment with a Cu (II) concentration of 0.5 mg/L, which was 30.1% higher than that of the 2.5 mg/L group. C. vulgaris had higher removal efficiencies of Cu (II) at a Cu (II) concentration of 0.1~1.5 mg/L. The-OH, C=O, -COOH, and C-O groups on the surface of the algal cells play a significant role in the removal of Cu (II). The removal rates of COD, NH3-N, TN, and TP by C. vulgaris at a Cu (II) concentration of 0.5 mg/L were the highest, which were 89.0%, 53.7%, 69.6%, and 47.3%, respectively.

Machine learning identifies the risk of complications after laparoscopic radical gastrectomy for gastric cancer.

BACKGROUND: Laparoscopic radical gastrectomy is widely used, and perioperative complications have become a highly concerned issue. AIM: To develop a predictive model for complications in laparoscopic radical gastrectomy for gastric cancer to better predict the likelihood of complications in gastric cancer patients within 30 days after surgery, guide perioperative treatment strategies for gastric cancer patients, and prevent serious complications. METHODS: In total, 998 patients who underwent laparoscopic radical gastrectomy for gastric cancer at 16 Chinese medical centers were included in the training group for the complication model, and 398 patients were included in the validation group. The clinicopathological data and 30-d postoperative complications of gastric cancer patients were collected. Three machine learning methods, lasso regression, random forest, and artificial neural networks, were used to construct postoperative complication prediction models for laparoscopic distal gastrectomy and laparoscopic total gastrectomy, and their prediction efficacy and accuracy were evaluated. RESULTS: The constructed complication model, particularly the random forest model, could better predict serious complications in gastric cancer patients undergoing laparoscopic radical gastrectomy. It exhibited stable performance in external validation and is worthy of further promotion in more centers. CONCLUSION: Using the risk factors identified in multicenter datasets, highly sensitive risk prediction models for complications following laparoscopic radical gastrectomy were established. We hope to facilitate the diagnosis and treatment of preoperative and postoperative decision-making by using these models.

Association of CirAEs and Efficacy in NSCLC Patients Treated with PD-1/PD-L1: A Meta-analysis of Cohort Studies.

PURPOSE: To systematically evaluate the relationship between cutaneous immunerelated adverse events (cirAEs) and the efficacy of PD-1/PD-L1 in the treatment of non-small cell lung cancer (NSCLC) and to provide an evidence-based reference for the clinical application of PD-1/PD-L1 and safety evaluation. METHODS: Electronic databases (PubMed, Embase, Medline, Web of Science, and the Cochrane Library) were screened systematically to collect prospective or retrospective cohort studies on the correlation between cirAEs and efficacy of PD-1/PD-L1 in the treatment of NSCLC. RESULTS: A total of 3514 participants were included in 13 cohort studies (enclosing an ambidirectional cohort study). Outcomes revealed that compared with those patients with non cirAEs, patients suffering cirAEs were associated with significantly higher objective response rate (ORR) [risk ratio (RR): 1.74, 95% confidence interval (CI): 1.42-2.14, P<0.00001], longer progressionfree survival (PFS) [RR: 0.52, 95% CI: 0.45-0.60, P<0.00001], and longer overall survival (OS) [RR:0.46, 95% CI: 0.38-0.56]. Sensitivity analyses through the exclusion of one study at a time did not significantly influence the outcomes, indicating that the meta-analysis results were relatively robust. Furthermore, subgroup analyses revealed consistent results in the study design (prospective or retrospective cohort studies), as well as in the endpoint results (PFS and OS) of Kaplan-Meier curves or Cox proportional hazards regression for evaluable patients. CONCLUSION: Currently, evidence reveals that cirAEs development may be associated with a good prognosis and can be an early predictor of the efficacy of PD-1/PD-L1 in the treatment of NSCLC patients.

Shenxiang Suhe pill improves cardiac function through modulating gut microbiota and serum metabolites in rats after acute myocardial infarction.

CONTEXT: Shenxiang Suhe pill (SXSH), a traditional Chinese medicine, is clinically effective against coronary heart disease, but the mechanism of cardiac-protective function is unclear. OBJECTIVE: We investigated the cardiac-protective mechanism of SXSH via modulating gut microbiota and metabolite profiles. MATERIALS AND METHODS: Sprague-Dawley (SD) male rats were randomly divided into 6 groups (n = 8): Sham, Model, SXSH (Low, 0.063 g/kg; Medium, 0.126 g/kg; High, 0.252 g/kg), and Ato (atorvastatin, 20 mg/kg). Besides the Sham group, rats were modelled with acute myocardial infarction (AMI) by ligating the anterior descending branch of the left coronary artery (LAD). After 3, 7, 14 days' administration, ultrasound, H&E staining, serum enzymic assay, 16S rRNA sequencing were conducted to investigate the SXSH efficacy. Afterwards, five groups of rats: Sham, Model, Model-ABX (AMI with antibiotics-feeding), SXSH (0.126 g/kg), SXSH-ABX were administrated for 14 days to evaluate the gut microbiota-dependent SXSH efficacy, and serum untargeted metabolomics test was performed. RESULTS: 0.126 g/kg of SXSH intervention for 14 days increased ejection fraction (EF, 78.22%), fractional shortening (FS, 109.07%), and aortic valve flow velocities (AV, 21.62%), reduced lesion area, and decreased serum LDH (8.49%) and CK-MB (10.79%). Meanwhile, SXSH upregulated the abundance of Muribaculaceae (199.71%), Allobaculum (1744.09%), and downregulated Lactobacillus (65.51%). The cardiac-protective effect of SXSH was disrupted by antibiotics administration. SXSH altered serum metabolites levels, such as downregulation of 2-n-tetrahydrothiophenecarboxylic acid (THTC, 1.73%), and lysophosphatidylcholine (lysoPC, 4.61%). DISCUSSION AND CONCLUSION: The cardiac-protective effect and suggested mechanism of SXSH could provide a theoretical basis for expanding its application in clinic.

FN1 mRNA 3'-UTR supersedes traditional fibronectin 1 in facilitating the invasion and metastasis of gastric cancer through the FN1 3'-UTR-let-7i-5p-THBS1 axis.

Background: Current clinical treatments for gastric cancer (GC), particularly advanced GC, lack infallible therapeutic targets. The 3'-untranslated region (3'-UTR) has attracted increasing attention as a drug target. Methods: In vitro and in vivo experiments were conducted to determine the function of FN1 3'-UTR and FN1 protein in invasion and metastasis. RNA pull-down assay and high-throughput sequencing were used to screen the factors regulated by FN1 3'-UTR and construct the regulatory network. Western blotting and polymerase chain reaction were used to examine the correlation of intermolecular expression levels. RNA-binding protein immunoprecipitation was used to verify the correlation between FN1 3'-UTR and target mRNAs. Results: The FN1 3'-UTR may have stronger prognostic implications than the FN1 protein in GC patients. Upregulation of FN1 3'-UTR significantly promoted the invasive and metastatic abilities of GC cells to a greater extent than FN1 protein in vitro and in vivo. A novel regulatory network was constructed based on the FN1 3'-UTR-let-7i-5p-THBS1 axis, wherein FN1 3'-UTR displayed stronger oncogenic effects than the FN1 protein. Conclusions: FN1 3'-UTR may be a better therapeutic target for constructing targeted drugs in GC than the FN1 protein.

An interval-valued carbon price forecasting method based on web search data and social media sentiment.

Accurate carbon price prediction is a crucial task for the carbon trading market. Previous studies have ignored the impact of online data and are limited to point predictions, which brings challenges to the accurate forecasting of carbon prices. To address those issues, this paper proposes an interval-valued carbon price forecasting method based on web search data and social media sentiment. First, we collect web search data and social media sentiment to improve prediction performance by synthesizing multiple types of data information. Second, we employ principal component analysis (PCA) to preprocess high-dimensional web search data, and utilize BosonNLP for quantifying social media information, thereby enhancing the predictability of the dataset. Subsequently, a variational mode decomposition (VMD) is applied to the carbon price and online data, followed by utilizing particle swarm optimization support vector regression (PSO-SVR) to predict each sub-modes and summing them up to obtain the ultimate forecasting outcome. Finally, using carbon prices in Guangdong and Hubei provinces as case studies, the experimental results demonstrate that web search data and social media sentiment significantly enhance the predictive accuracy of interval-valued carbon prices. Furthermore, the proposed VMD-PSO-SVR outperforms other comparative models in the accuracy and reliability of interval-valued forecasting.

Miniaturized matrix solid-phase dispersion and solid-phase clear-up combined with capillary electrophoresis for efficient determination of trace bioactive components in complicated sample matrix: Take Wubi Shanyao Pill as an example.

Accurate quantitative analysis of trace analytes in a complicated matrix is a challenge in modern analytical chemistry. An appropriate analytical method is considered to be one of the most common gaps during the whole process. In this study, a green and efficient strategy based on miniaturized matrix solid-phase dispersion and solid-phase extraction combined with capillary electrophoresis was first proposed for extracting, purifying and determining target analytes from complicated matrix, using Wubi Shanyao Pill as an example. In detail, 60 mg of samples were dispersed on MCM-48 to obtain high yields of analytes, then the extract was purified with a solid-phase extraction cartridge. Finally, four analytes in the purified sample solution were determined by capillary electrophoresis. The parameters affecting the extraction efficiency of matrix solid-phase dispersion, purification efficiency of solid-phase extraction and separation effect of capillary electrophoresis were investigated. Under the optimized conditions, all analytes demonstrated satisfactory linearity (R2 >0.9983). What's more, the superior green potential of the developed method for the determination of complex samples was confirmed by the Analytical GREEnness Metric Approach. The established method was successfully applied in the accurate determination of target analytes in Wubi Shanyao Pill and thus provided reliable, sensitive, and efficient strategy support for its quality control.

Self-assembled short peptides: Recent advances and strategies for potential pharmaceutical applications.

Self-assembled short peptides have intrigued scientists due to the convenience of synthesis, good biocompatibility, low toxicity, inherent biodegradability and fast response to change in the physiological environment. Therefore, it is necessary to present a comprehensive summary of the recent advances in the last decade regarding the construction, route of administration and application of self-assembled short peptides based on the knowledge on their unique and specific ability of self-assembly. Herein, we firstly explored the molecular mechanisms of self-assembly of short peptides, such as non-modified amino acids, as well as Fmoc-modified, N-functionalized, and C-functionalized peptides. Next, cell penetration, fusion, and peptide targeting in peptide-based drug delivery were characterized. Then, the common administration routes and the potential pharmaceutical applications (drug delivery, antibacterial activity, stabilizers, imaging agents, and applications in bioengineering) of peptide drugs were respectively summarized. Last but not least, some general conclusions and future perspectives in the relevant fields were briefly listed. Although with certain challenges, great opportunities are offered by self-assembled short peptides to the fascinating area of drug development.

Regulating the Solvation Shell Structure of Lithium Ions for Smooth Li Metal Deposition in Quasi-Solid-State Batteries.

Gel polymer electrolytes (GPE) are promising next-generation electrolytes for high-energy batteries, combining the multiple advantages of liquid and all-solid-state electrolytes. Herein, we a synthesized GPE using poly(ethylene glycol)acrylate (PEGDA) in order to understand how the GPE efficiently inhibits lithium dendrite formation and growth. The effects of PEGDA on the solvation shell structure of the lithium ion are investigated using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations, which are also supported by Raman spectroscopy. The GPE electrolytes with optimal PEGDA concentration exhibit high transference numbers (t Li + ${{_{{\rm Li}{^{+}}}}}$ =0.72) and ionic conductivity (σ=3.24 mS cm-1 ). A symmetric lithium ion battery using GPE can be stably cycled for 1200 h in comparison to 320 h in a liquid electrolyte (LE), possibly owing to the high content of LiF (17.9 %) in the solid-electrolyte interphase film of the GPE cell. The observed concentration/electric field gradient observed through the finite element method also accounts for the good cycling performance. In addition, a LiCoO2 |GPE|Li cell demonstrates excellent capacity retention of 87.09 % for 200 cycles; this approach could present promising guidelines for the design of high-energy lithium batteries.

d-p Hybridization-Induced "Trapping-Coupling-Conversion" Enables High-Efficiency Nb Single-Atom Catalysis for Li-S Batteries.

Single-atom catalysts have been paid more attention to improving sluggish reaction kinetics and anchoring polysulfide for lithium-sulfur (Li-S) batteries. It has been demonstrated that d-block single-atom elements in the fourth period can chemically interact with the local environment, leading to effective adsorption and catalytic activity toward lithium polysulfides. Enlightened by theoretical screening, for the first time, we design novel single-atom Nb catalysts toward improved sulfur immobilization and catalyzation. Calculations reveal that Nb-N4 active moiety possesses abundant unfilled antibonding orbitals, which promotes d-p hybridization and enhances anchoring capability toward lithium polysulfides via a "trapping-coupling-conversion" mechanism. The Nb-SAs@NC cell exhibits a high capacity retention of over 85% after 1000 cycles, a superior rate performance of 740 mA h g-1 at 7 C, and a competitive areal capacity of 5.2 mAh cm-2 (5.6 mg cm-2). Our work provides a new perspective to extend cathodes enabling high-energy-density Li-S batteries.

Pollutant removal from swine wastewater and kinetics in constructed rapid infiltration system (CRI system).

The purpose of this paper is centred on the kinetics of removal of main pollutants in wastewater and to compared different hydraulic loading conditions of the constructed rapid infiltration system (CRI system) in terms of removal efficiencies, effluent concentrations, mass removal rate (MRR), and the first-order removal rate coefficient (k) of COD, TOC, NH4+-N, TN, and TP. The results showed that the higher the hydraulic loading, the higher the effluent concentration. The results that synthesized hydraulic loading, effluent concentrations, removal efficiencies, and other conditions showed that the best hydraulic loading was 40 cm/d. When the hydraulic load was 40 cm/d, the effluent average concentrations of COD, TOC, NH4+-N, TN, TP, Cu2+ and the removal efficiencies were 27.31 ± 16.40 mg/L, 86.11%, 10.55 ± 5.25 mg/L, 84.64%, 0.59 ± 0.87 mg/L, 99.60%, 143.31 ± 14.77 mg/L, 7.04%, 5.64 ± 1.38 mg/L, 79.20%, and 0.13 ± 0.47 mg/L, 97.51%, respectively. According to a kinetic study of the primary pollutants, the MRR increased with an increase in the hydraulic loading, except for ammonia nitrogen. CRI-3, CRI-4 were high significant correlated with ammonia nitrogen (with R2 = 93.65% and R2 = 95.03%, respectively), while CRI-2, CRI-3, and CRI-4 were high significant correlated with total nitrogen (with R2 = 94.56%, R2 = 96.70% and R2 = 96.56% respectively).

Finite-Time Stability Control of Uncertain Nonlinear Systems With Self-Limiting Control Terms.

In this brief, we define a self-limiting control term, which has the function of guaranteeing the boundedness of variables. Then, we apply it to a finite-time stability control problem. For nonstrict feedback nonlinear systems, a finite-time adaptive control scheme, which contains a piecewise differentiable function, is proposed. This scheme can eliminate the singularity of derivative of a fractional exponential function. By adding a self-limiting term to the controller and the virtual control law of each subsystem, the boundedness of the overall system state is guaranteed. Then the unknown continuous functions are estimated by neural networks (NNs). The output of the closed-loop system tracks the desired trajectory, and the tracking error converges to a small neighborhood of the equilibrium point in finite time. The theoretical results are illustrated by a simulation example.